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| Status |
Public on Apr 19, 2021 |
| Title |
Predicting Master Transcription Factors from Pan-Cancer Expression Data |
| Organism |
Homo sapiens |
| Experiment type |
Expression profiling by high throughput sequencing
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| Summary |
Critical developmental “master transcription factors” (MTFs) can be subverted during tumorigenesis to control expression of oncogenic transcriptional programs. Current approaches to identify MTFs rely on chromatin immunoprecipitation-sequencing data, which is currently unavailable for many cancer types. We developed the CaCTS (Cancer Core Transcription factor Specificity) algorithm to prioritize candidate MTFs using pan-cancer RNA-sequencing data. CaCTS identified candidate MTFs across 34 tumor types and 140 subtypes, including known MTFs. We also made novel predictions, including for cancer types/subtypes for which MTFs are unknown. This included PAX8, SOX17, and MECOM as candidate MTFs in ovarian cancer (OV). In OV cells, these factors are required for viability, lie proximal to super-enhancers, co-occupy regulatory elements globally and co-bind at critical gene loci encoding OV biomarkers. Identification of tumor MTFs, especially for tumor types with limited understanding of transcriptional drivers, paves the way to therapeutic targeting of MTFs in a broad spectrum of cancers.
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| Overall design |
RNA-seq results of OVCAR4 cells treated with si controls, siPAX8, siSOX17,siDual(siPAX8/siSOX17), siMECOM, or siWT1
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| Contributor(s) |
Reddy J, Fonsseca MA, Corona RI, Nameki R, Dezem FS, Chang H, Lin X, Abbasi F, Abraham BJ, Lawrenson K |
| Citation(s) |
33852846, 34818047 |
| Submission date |
May 12, 2020 |
| Last update date |
Dec 15, 2021 |
| Contact name |
Robbin Nameki |
| E-mail(s) |
Robbin.Nameki@cshs.org, Robbinnameki4@gmail.com
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| Organization name |
Cedars-Sinai Medical Center
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| Department |
Obstetrics and Gynecology
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| Lab |
Lawrenson
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| Street address |
8700 Beverly Blvd
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| City |
Los Angeles |
| State/province |
CA |
| ZIP/Postal code |
90048 |
| Country |
USA |
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| Platforms (1) |
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| Samples (14)
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| Relations |
| BioProject |
PRJNA632047 |
| SRA |
SRP261351 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE150443_typecounts_geo_1.txt.gz |
5.2 Mb |
(ftp)(http) |
TXT |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data are available on Series record |
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